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Minority Rules: Scientists Discover Tipping Point for the Spread of Ideas

Mon, 2011-07-25 16:53 -- Anonymous

July 25, 2011

In this visualization, we see the
tipping point where minority opinion (shown in red)
quickly becomes majority opinion. Over time, the minority
opinion grows. Once the minority opinion reached 10
percent of the population, the network quickly changes as
the minority opinion takes over the original majority
opinion (shown in green).
Image credit: SCNARC/Rensselaer Polytechnic
Institute.

Scientists at Rensselaer Polytechnic Institute have found
that when just 10 percent of the population holds an unshakable
belief, their belief will always be adopted by the majority of
the society. The scientists, who are members of the Social Cognitive Networks
Academic Research Center (SCNARC) at Rensselaer, used
computational and analytical methods to discover the tipping
point where a minority belief becomes the majority opinion. The
finding has implications for the study and influence of
societal interactions ranging from the spread of innovations to
the movement of political ideals.

“When the number of committed opinion holders is below 10
percent, there is no visible progress in the spread of ideas.
It would literally take the amount of time comparable to the
age of the universe for this size group to reach the majority,”
said SCNARC Director Boleslaw
Szymanski, the Claire and Roland Schmitt Distinguished
Professor at Rensselaer. “Once that number grows above 10
percent, the idea spreads like flame.”

As an example, the ongoing events in Tunisia and Egypt
appear to exhibit a similar process, according to Szymanski.
“In those countries, dictators who were in power for decades
were suddenly overthrown in just a few weeks.”

An important aspect of the finding is that the percent of
committed opinion holders required to shift majority opinion
does not change significantly regardless of the type of network
in which the opinion holders are working. In other words, the
percentage of committed opinion holders required to influence a
society remains at approximately 10 percent, regardless of how
or where that opinion starts and spreads in the society.

To reach their conclusion, the scientists developed computer
models of various types of social networks. One of the networks
had each person connect to every other person in the network.
The second model included certain individuals who were
connected to a large number of people, making them opinion hubs
or leaders. The final model gave every person in the model
roughly the same number of connections. The initial state of
each of the models was a sea of traditional-view holders. Each
of these individuals held a view, but were also, importantly,
open minded to other views.

Once the networks were built, the scientists then
“sprinkled” in some true believers throughout each of the
networks. These people were completely set in their views and
unflappable in modifying those beliefs. As those true believers
began to converse with those who held the traditional belief
system, the tides gradually and then very abruptly began to
shift.

“In general, people do not like to have an unpopular opinion
and are always seeking to try locally to come to consensus. We
set up this dynamic in each of our models,” said SCNARC
Research Associate and corresponding paper author Sameet
Sreenivasan. To accomplish this, each of the individuals in the
models “talked” to each other about their opinion. If the
listener held the same opinions as the speaker, it reinforced
the listener’s belief. If the opinion was different, the
listener considered it and moved on to talk to another person.
If that person also held this new belief, the listener then
adopted that belief.

“As agents of change start to convince more and more people,
the situation begins to change,” Sreenivasan said. “People
begin to question their own views at first and then completely
adopt the new view to spread it even further. If the true
believers just influenced their neighbors, that wouldn’t change
anything within the larger system, as we saw with percentages
less than 10.”

The research has broad implications for understanding how
opinion spreads. “There are clearly situations in which it
helps to know how to efficiently spread some opinion or how to
suppress a developing opinion,” said Associate Professor of
Physics and co-author of the paper Gyorgy Korniss.
“Some examples might be the need to quickly convince a town to
move before a hurricane or spread new information on the
prevention of disease in a rural village.”

The researchers are now looking for partners within the
social sciences and other fields to compare their computational
models to historical examples. They are also looking to study
how the percentage might change when input into a model where
the society is polarized. Instead of simply holding one
traditional view, the society would instead hold two opposing
viewpoints. An example of this polarization would be Democrat
versus Republican.

The research is part of a much larger body of work taking
place under SCNARC at Rensselaer. The center joins researchers
from a broad spectrum of fields – including sociology, physics,
computer science, and engineering – in exploring social
cognitive networks. The center studies the fundamentals of
network structures and how those structures are altered by
technology. The goal of the center is to develop a deeper
understanding of networks and a firm scientific basis for the
newly arising field of network science. More information on the
launch of SCNARC can be found at
http://news.rpi.edu/update.do?artcenterkey=2721&setappvar=page(1)

Szymanski, Sreenivasan, and Korniss were joined in the
research by Professor of Mathematics Chjan Lim, and graduate
students Jierui Xie (first author) and Weituo Zhang.

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